Providing a repository of audio files having pronunciations for text strings to provide to a speech synthesizer

The present invention relates to a computer program product, system, and method for providing a repository of audio files having pronunciations for text strings to provide to a speech synthesizer.

A speech synthesizer converts normal language text into speech using a text-to-speech algorithm. The speech synthesizer produces output speech audio by concatenating pieces of recorded speech determined for units of the text in the document. Users may customize the speech produced by the speech synthesizer by annotating a document to subject to speech synthesis with predefined audio to use for certain text strings in the document when the user wants the speech synthesizer to use a specified audio output over the sounds the speech synthesizer would produce by default. Speech Synthesis Markup Language (SSML) is an XML-based markup language for speech synthesis applications. Users may encode a document with SSML statements that provide audio for the speech synthesizer to use for certain defined text strings when converting text to speech in the document.

There is a need in the art to provide improved techniques for providing audio for a speech synthesizer to use when converting text to speech.

Provided are a computer program product, system, and method for providing a repository of audio files having pronunciations for text strings to provide to a speech synthesizer. The repository has data structures for text strings in documents. A data structure for a text string in a document indicates at least one attribute of a presentation of the text string in the document and at least one audio file providing at least one audio pronunciation of the text string. A search text string and a search attribute are received from the speech synthesizer. A determination is made of a data structure in the repository including a text string and an attribute matching the search text string and the search attribute, respectively. An audio file, indicated in the determined data structure, is returned to the speech synthesizer to output for the search text string in a document being processed by the speech synthesizer.

Speech synthesizers may produce pronunciations for certain types of text strings, such as abbreviations and acronyms, that are not the common expected pronunciation in the particular category or language of the text being converted to speech. For instance, in the category of information technology, the text string “IEEE” is an abbreviation/acronym for the “Institute of Electrical and Electronics Engineers”. A speech synthesizer may produce a pronunciation based on the phonetics that is not the expected pronunciation of that acronym in the category of information technology, such as “I Triple E”. Currently, a user may encode the document to speech synthesize with an annotation providing the correctly understood pronunciation of this acronym IEEE. However, relying on user inserted annotations to provide a correct pronunciation for an acronym can be tedious for the user to have to annotate documents. Further, many documents to speech synthesize may not include annotations providing correct pronunciations for abbreviations and acronyms given the context of the document/text.

Described embodiments provide improvements to speech synthesis technology by providing a repository of pronunciation data structures having audio files including pronunciations for a specific type of text strings that speech synthesizers may not convert to speech in an acceptable manner, such as abbreviations and acronyms. These pronunciation data structures having the pronunciation audio files for a text string may further include attributes for the presentation of the text string in the audio file, such as category and language. When the speech synthesizer detects this specific type of text string, such as abbreviations and acronyms, for which the repository provides pronunciations, then the speech synthesizer may send a pronunciation query to a pronunciation server to query the repository to determine a pronunciation data structure having the attributes and text string of the pronunciation query that will provide an audio file having a user acceptable pronunciation of the text string for the category. This allows the speech synthesizer to produce accurate and commonly understood pronunciations of acronyms and abbreviations that the speech synthesizer's default text-to-speech conversion would not pronounce in a commonly understood manner. This allows the speech synthesizer to produce pronunciations that are commonly understood in a particular language and category of use.

The described embodiments provide further improvements to speech synthesis technology by providing technology to collect and harvest pronunciation audio files providing pronunciations for specific types of strings, such as abbreviations and acronyms. Described embodiments provide technology to harvest audio files for specific types of text strings from network sites, such as web sits on the Internet or local network sites and locations, from a closed caption transcription of an audio file that provides pronunciations for the specific type of text string, e.g., abbreviations and pronunciations, and from user supplied annotations in the text to convert to speech.

illustrates an embodiment of a pronunciation serverin communication with a client systemover a network. The clientincludes a speech synthesizer, such a text-to-speech system, to convert text strings in a document, comprising a collection of text, to speech or audio output. The speech synthesizerwhen processing a specified type of text string, such as an abbreviation or acronym, in a text documentmay generate a pronunciation query, such as in the form of an Application Programming Interface (API), to request an audio file, such as a digital audio file, that provides a pronunciation for the specified text string. The pronunciation serverincludes components to process the pronunciation query, including a pronunciation engineto receive the pronunciation queryand invoke a repository searcherto search a pronunciation repositoryfor a pronunciation data structure() providing an audio file for the text string and search attributes, such as language and category, included in the pronunciation query.

The pronunciation servermay further include a pronunciation collectorto gather information on digital audio files providing pronunciations for specified text strings, such as acronyms/abbreviations, to include in the pronunciation repository. For instance, the pronunciation collectormay process certain web sites and network locations providing audio files of pronunciations for abbreviations/acronyms to add to the pronunciation repository, such as described with respect to. The pronunciation collectormay also process a closed caption transcription of an audio file text synchronized with audio segments in the audio file to determine audio segments for the text strings to add to the pronunciation repository, such as described with respect to. The pronunciation collectormay also receive user annotations embedded in the document/textspecifying audio files to use for specified text strings, such as abbreviations or annotations. The annotations may comprise Speech Synthesis Markup Language (SSML) statements that allow the user to encode the textsubject to text-to-speech conversion with specified audio files to use to pronounce the terms in the documentand not rely on the native speech synthesizerpronunciation, as described with respect to.

The pronunciation collectormay invoke a pronunciation repository updaterto determine whether the repositoryincludes a data structurefor the text string and attributes for the collected audio file or whether a new data structureneeds to be created for the collected audio file. The pronunciation repository updatermay update any pre-existing data structure for the text string with information on the collected audio file or create a new data structureif there is not one for the text string and attributes of the collected audio file.

The networkmay comprise a network such as a Storage Area Network (SAN), Local Area Network (LAN), Intranet, the Internet, Wide Area Network (WAN), peer-to-peer network, wireless network, arbitrated loop network, etc.

The arrows shown inbetween the components and objects in the pronunciation serverand the clientrepresent a data flow between the components.

Generally, program modules, such as the program components,,,,may comprise routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. The program components and hardware devices of the computing devicesandofmay be implemented in one or more computer systems, where if they are implemented in multiple computer systems, then the computer systems may communicate over a network.

The program components,,,,may be accessed by a processor from memory to execute. Alternatively, some or all of the program components,,,,may be implemented in separate hardware devices, such as Application Specific Integrated Circuit (ASIC) hardware devices.

The functions described as performed by the program,,,,may be implemented as program code in fewer program modules than shown or implemented as program code throughout a greater number of program modules than shown.

The program components described as implemented in the pronunciation servermay be implemented in the speech synthesizeror at the client system.

The client computermay comprise a personal computing device, such as a laptop, desktop computer, tablet, smartphone, etc. The servermay comprise one or more server class computing devices, or other suitable computing devices. The systemsandmay comprise physical machines or virtual machines.

illustrates an embodiment of a pronunciation querypresented by the speech synthesizerto request a digital audio pronunciation for a specified text string, such as an abbreviation or acronym, and includes: a search request identifier (ID); a search text stringfor which the pronunciation is to be provided, such as an abbreviation/acronym; a search categoryproviding a context of the document including the search text string, such as information technology, computer science, legal, sports, business, soccer, basketball, film industry, etc.; a search languageof the language of the search text string; and a result priorityindicating whether a highest priority audio file should be returned or if there are multiple audio files to return multiple of the highest priority audio files. A highest priority audio file may comprise an audio file having a most frequently noted audio file/pronunciation of a text string.

illustrates an embodiment of an instance of a pronunciation data structureindicating an audio file providing a pronunciation of a text string used in the presence of certain attributes, such as category and language. The pronunciation data structureincludes an identifier; a text string, such as an abbreviation/acronym; a categoryproviding a context in which the text stringwas used, such as a field of use, e.g., information technology, legal, sports, business, etc.; a languageof the text string; and one or more audio file recordsproviding pronunciations for the text stringfor the categoryand language. An audio file recordmay indicate a digital audio fileproviding the pronunciation and a countindicating a number of times the pronunciation in the audio filewas located by the pronunciation collectorfor the text stringin the context of the categoryand language. The indication of the audio filemay comprise a link or address to the digital audio file in a network accessible storage location or comprise the digital audio file itself.

In, the attributes associated with the use of the pronunciation in the audio fileused for the text stringcomprises category, e.g., field of use, and language. In alternative implementations, additional or different attributes of the context in which the pronunciation recorded in the audio fileis used for the text stringmay be provided. Additional attributes may include user profile attributes of users to which the text is directed, etc. Further, in described embodiments, the pronunciation data structureis provided for text strings comprising abbreviations or acronyms. In additional embodiments, the text string may comprise other specified types of text strings and is not limited to abbreviations/acronyms.

shows one implementation of the pronunciation data structure. In alternative embodiments, the data structures and fields used to represent the information in the pronunciation data structuremay be represented in different data arrangements, such as in different database records and objects that provide the association of data shown in.

illustrates an embodiment of operations performed by the pronunciation repository updaterto update a pronunciation data structurealready in the repositoryor add a new pronunciation data structureto the repositorybased on a digital audio file located by the pronunciation collectorproviding a pronunciation for a text string. Upon receiving (at block) an audio file providing a pronunciation of a text string, e.g., abbreviation/acronym, category, and language from the pronunciation collectoror other source, the pronunciation repository updatersearches (at block) the repositoryfor a matching pronunciation data structurehaving the received search text string, category, and search languagefor the received audio file. If (at block) a matching pronunciation data structureis not located that satisfies the search parameters, then a pronunciation data structureis added (at block) to the repositoryhaving the text string, categoryand languageprovided for the received audio file. The pronunciation repository updaterfurther adds (at block) an audio file recordto the new pronunciation data structureincluding the indication of the audio fileand a countset to indicate one instance of the audio filewas located.

If (at block) there is a matching pronunciation data structurein the repositorysatisfying the search request, then a determination is made (at block) whether the matching pronunciation data structureindicates in audio file fieldan audio file matching the received audio file. If (at block) there is a matching audio file, then the countin the audio file recordhaving the matching audio fileis incremented (at block) by one. If (at block) there is no matching pronunciation data structurematching the search request, then control proceeds to blockto add a pronunciation data structureto the repository for the located new audio file.

With the embodiment of, upon collecting or receiving a new audio file for a text string, such as an abbreviation/acronym, and attributes of the use of the pronunciation for the text string, the repositoryis updated to increase a count if that received audio file is already indicated in a pronunciation data structureor a new pronunciation data structureis added to the repositoryso that the repository retains all received audio files providing pronunciations for a specified type of text string and a frequency that particular pronunciation, as recorded in the received audio file, is detected. This ensures that the most frequently used pronunciations for a text string type, such as an acronym/abbreviation, are maintained and indicated as such in the repositoryand available to provide to the speech synthesizerwhen needed to convert text-to-speech.

illustrates an embodiment of operations performed by the pronunciation collectorto gather audio files having pronunciations of text strings from a network location, such as a web site. The pronunciation collectormay be configured to process specific web site addresses known to have pronunciations for abbreviations/acronyms, or crawl the World Wide Web looking for web sites having audio files providing pronunciations of abbreviations/acronyms. Upon initiating (at block) operations on a web site or network location having audio files with pronunciations, the pronunciation collectordetermines (at block) an audio file on the web site providing a pronunciation of a text string, such as an abbreviation or acronym. The pronunciation collectorthen determines (at block) attributes of the located audio file, such as language and category. The attributes may be provided with metadata of the audio file or may be determined by the pronunciation collectorperforming natural language processing (NLP) of the web site to determine the attributes of the located audio file. In such case, the pronunciation collectormay implement NLP processing algorithms and capabilities. The pronunciation collectormay then call (at block) the pronunciation repository updaterto perform the operations into include information on the determined audio file in a pronunciation data structure(existing or new) in the repository having the abbreviation/acronym text string and determined attributes (e.g., category and language).

illustrates an embodiment of operations performed by the pronunciation collectorto determine pronunciations from audio segments in an audio file synchronized with closed captions in a transcription of an audio file. Upon initiating (at block) operations to harvest pronunciations from closed captions synchronized with audio segments in an audio file, the pronunciation collectorprocesses (at block) closed captions in a transcription of an audio file to determine abbreviations or acronyms, or other specified strings, in the transcription, which comprises text converted from the digital audio file. The pronunciation collectordetermines (at block) attributes of the audio/closed caption file, such as language and category. This information may be determined by determining the language of the audio file. The attributes of the audio file, such as category and language, may be determined by natural language processing of the closed caption transcription to determine a category or from metadata associated with the audio file.

For each determined abbreviation and acronym text string identified in the closed caption transcription, the pronunciation collectordetermines (at block) audio segments in the audio file providing pronunciations of the abbreviations and acronyms in the closed caption file, where the text in the closed caption file is synchronized to audio providing speech for the closed captions. The pronunciation collectormay then call (at block) the pronunciation repository updaterto perform the operations into include, in a pronunciation data structure(existing or new) in the repository, information on the audio segments in the audio file that synchronize to abbreviation/acronym strings in the closed caption file. The pronunciation data structureincludes the abbreviation/acronymand determined categoryand language, along with the audio segment.

illustrates an embodiment of operations performed by the pronunciation collectorto include information on an audio file for a pronunciation indicated with an annotation included in a document being processed by a speech synthesizer. The annotation may be encoded with SSML embedded by a user in the document subject to the text-to-speech conversion. The SSML annotation may be provided by the speech synthesizerwhen processing the documentincluding the text to translate to speech. The annotation indicates the text string, abbreviation/acronym, the audio file to pronounce the text string, and may indicate the language and category. Upon receiving (at block), from the speech synthesizer, a speech synthesis markup language (SSML) annotation, embedded in the documentprocessed by the speech synthesizer, the pronunciation collectordetermines (at block) attributes of the document, such as language and category. This information may be provided by the speech synthesizer. The pronunciation collectorperforms (at block) the operations into include information on the audio file indicated in the annotation in a pronunciation data structure(existing or new) in the repositoryhaving the abbreviation/acronym text string in the annotation and the determined attributes (e.g., category and language).

With the operations of, the pronunciation collectormay gather pronunciations for abbreviations and acronyms from different locations to include in pronunciation data structuresin the repositoryto use for text-to-speech conversion of the located abbreviations and acronyms. Further, by accessing duplicate pronunciations matching information in data structures in the repository, the pronunciation collectormay update the countor frequency values indicating a number of time pronunciations in audio files were used or located for the same text string, category, and language. This gathered frequency informationmay be used to determine a priority of the audio filesin the pronunciation data structurefor the text string.

illustrates an embodiment of operations performed by the pronunciation engineand repository searcherto process a pronunciation queryfrom the speech synthesizer. Upon receiving (at block) a pronunciation queryfrom the speech synthesizerincluding a search text string, search attribute (e.g., categoryand languageof documentbeing processed), and result priority, the pronunciation engineinvokes (at block) the repository searcherto search the repositoryfor a pronunciation data structurehaving the search attribute(s),and the search text stringin the received pronunciation query. If (at block) there is no pronunciation data structurereturned in response to the search, then the pronunciation enginereturns (at block) a reply that no pronunciation is available in the repository. In such case, the speech synthesizer, upon receiving that reply of no available pronunciation, may synthesize the text with its native algorithm to produce speech. If (at block) a pronunciation data structureis returned, then the pronunciation enginedetermines (at block) whether the result priorityindicates to return the highest priority audio file. If (at block) the request is for only the highest priority audio file for the pronunciation, then the pronunciation enginereturns (at block) to the speech synthesizer, as a search result for the search text string, the audio filein the audio file recordin the returned pronunciation data structurehaving a highest priority or highest count. If (at block) the result priorityin the queryindicates to return multiple of highest priority audio files, then the pronunciation enginereturns a number of audio files for the search text string of highest priority to satisfy the result priority.

With the embodiment of, the pronunciation engine processes a request from a speech synthesizer for a better or more accurate pronunciation for an abbreviation or acronym in the text than would be provided by the speech synthesizer. The pronunciation enginedetermines the most frequently accessed audio filefor the pronunciation data structurehaving the provided attributes (e.g., category and language). This most frequently accessed or common pronunciation/audio filemay be returned to the speech synthesizerto use to convert the specified abbreviation or acronym, or other text, to speech.

The present invention may be a system, a method, and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention.

Various aspects of the present disclosure are described by narrative text, flowcharts, block diagrams of computer systems and/or block diagrams of the machine logic included in computer program product (CPP) embodiments. With respect to any flowcharts, depending upon the technology involved, the operations can be performed in a different order than what is shown in a given flowchart. For example, again depending upon the technology involved, two operations shown in successive flowchart blocks may be performed in reverse order, as a single integrated step, concurrently, or in a manner at least partially overlapping in time.

A computer program product embodiment (“CPP embodiment” or “CPP”) is a term used in the present disclosure to describe any set of one, or more, storage media (also called “mediums”) collectively included in a set of one, or more, storage devices that collectively include machine readable code corresponding to instructions and/or data for performing computer operations specified in a given CPP claim. A “storage device” is any tangible device that can retain and store instructions for use by a computer processor. Without limitation, the computer readable storage medium may be an electronic storage medium, a magnetic storage medium, an optical storage medium, an electromagnetic storage medium, a semiconductor storage medium, a mechanical storage medium, or any suitable combination of the foregoing. Some known types of storage devices that include these mediums include: diskette, hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), static random access memory (SRAM), compact disc read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanically encoded device (such as punch cards or pits/lands formed in a major surface of a disc) or any suitable combination of the foregoing. A computer readable storage medium, as that term is used in the present disclosure, is not to be construed as storage in the form of transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide, light pulses passing through a fiber optic cable, electrical signals communicated through a wire, and/or other transmission media. As will be understood by those of skill in the art, data is typically moved at some occasional points in time during normal operations of a storage device, such as during access, de-fragmentation or garbage collection, but this does not render the storage device as transitory because the data is not transitory while it is stored.

Computing environmentcontains an example of an environment for the execution of the pronunciation serverprogram components, including program components,,, and(), involved in performing the operations to maintain and provide pronunciations for abbreviations and acronyms.

In addition to block, computing environmentincludes, for example, computer, wide area network (WAN), end user device (EUD), remote server, public cloud, and private cloud. In this embodiment, computerincludes processor set(including processing circuitryand cache), communication fabric, volatile memory, persistent storage(including operating systemand block, as identified above), peripheral device set(including user interface (UI) device set, storage, and Internet of Things (IoT) sensor set), and network module. Remote serverincludes remote database. Public cloudincludes gateway, cloud orchestration module, host physical machine set, virtual machine set, and container set.

COMPUTERmay take the form of a desktop computer, laptop computer, tablet computer, smart phone, smart watch or other wearable computer, mainframe computer, quantum computer or any other form of computer or mobile device now known or to be developed in the future that is capable of running a program, accessing a network or querying a database, such as remote database. As is well understood in the art of computer technology, and depending upon the technology, performance of a computer-implemented method may be distributed among multiple computers and/or between multiple locations. On the other hand, in this presentation of computing environment, detailed discussion is focused on a single computer, specifically computer, to keep the presentation as simple as possible. Computermay be located in a cloud, even though it is not shown in a cloud in. On the other hand, computeris not required to be in a cloud except to any extent as may be affirmatively indicated.

PROCESSOR SETincludes one, or more, computer processors of any type now known or to be developed in the future. Processing circuitrymay be distributed over multiple packages, for example, multiple, coordinated integrated circuit chips. Processing circuitrymay implement multiple processor threads and/or multiple processor cores. Cacheis memory that is located in the processor chip package(s) and is typically used for data or code that should be available for rapid access by the threads or cores running on processor set. Cache memories are typically organized into multiple levels depending upon relative proximity to the processing circuitry. Alternatively, some, or all, of the cache for the processor set may be located “off chip.” In some computing environments, processor setmay be designed for working with qubits and performing quantum computing.

Computer readable program instructions are typically loaded onto computerto cause a series of operational steps to be performed by processor setof computerand thereby effect a computer-implemented method, such that the instructions thus executed will instantiate the methods specified in flowcharts and/or narrative descriptions of computer-implemented methods included in this document (collectively referred to as “the inventive methods”). These computer readable program instructions are stored in various types of computer readable storage media, such as cacheand the other storage media discussed below. The program instructions, and associated data, are accessed by processor setto control and direct performance of the inventive methods. In computing environment, at least some of the instructions for performing the inventive methods may be stored in persistent storage.

COMMUNICATION FABRICis the signal conduction path that allows the various components of computerto communicate with each other. Typically, this fabric is made of switches and electrically conductive paths, such as the switches and electrically conductive paths that make up busses, bridges, physical input/output ports and the like. Other types of signal communication paths may be used, such as fiber optic communication paths and/or wireless communication paths.

VOLATILE MEMORYis any type of volatile memory now known or to be developed in the future. Examples include dynamic type random access memory (RAM) or static type RAM. Typically, volatile memoryis characterized by random access, but this is not required unless affirmatively indicated. In computer, the volatile memoryis located in a single package and is internal to computer, but, alternatively or additionally, the volatile memory may be distributed over multiple packages and/or located externally with respect to computer.

PERSISTENT STORAGEis any form of non-volatile storage for computers that is now known or to be developed in the future. The non-volatility of this storage means that the stored data is maintained regardless of whether power is being supplied to computerand/or directly to persistent storage. Persistent storagemay be a read only memory (ROM), but typically at least a portion of the persistent storage allows writing of data, deletion of data and re-writing of data. Some familiar forms of persistent storage include magnetic disks and solid state storage devices. Operating systemmay take several forms, such as various known proprietary operating systems or open source Portable Operating System Interface-type operating systems that employ a kernel. The code included in blocktypically includes at least some of the computer code involved in performing the inventive methods.

PERIPHERAL DEVICE SETincludes the set of peripheral devices of computer. Data communication connections between the peripheral devices and the other components of computermay be implemented in various ways, such as Bluetooth connections, Near-Field Communication (NFC) connections, connections made by cables (such as universal serial bus (USB) type cables), insertion-type connections (for example, secure digital (SD) card), connections made through local area communication networks and even connections made through wide area networks such as the internet. In various embodiments, UI device setmay include components such as a display screen, speaker, microphone, wearable devices (such as goggles and smart watches), keyboard, mouse, printer, touchpad, game controllers, and haptic devices. Storageis external storage, such as an external hard drive, or insertable storage, such as an SD card. Storagemay be persistent and/or volatile. In some embodiments, storagemay take the form of a quantum computing storage device for storing data in the form of qubits. In embodiments where computeris required to have a large amount of storage (for example, where computerlocally stores and manages a large database) then this storage may be provided by peripheral storage devices designed for storing very large amounts of data, such as a storage area network (SAN) that is shared by multiple, geographically distributed computers. IoT sensor setis made up of sensors that can be used in Internet of Things applications. For example, one sensor may be a thermometer and another sensor may be a motion detector.

NETWORK MODULEis the collection of computer software, hardware, and firmware that allows computerto communicate with other computers through WAN. Network modulemay include hardware, such as modems or Wi-Fi signal transceivers, software for packetizing and/or de-packetizing data for communication network transmission, and/or web browser software for communicating data over the internet. In some embodiments, network control functions and network forwarding functions of network moduleare performed on the same physical hardware device. In other embodiments (for example, embodiments that utilize software-defined networking (SDN)), the control functions and the forwarding functions of network moduleare performed on physically separate devices, such that the control functions manage several different network hardware devices. Computer readable program instructions for performing the inventive methods can typically be downloaded to computerfrom an external computer or external storage device through a network adapter card or network interface included in network module.

WANis any wide area network (for example, the internet) capable of communicating computer data over non-local distances by any technology for communicating computer data, now known or to be developed in the future. In some embodiments, the WANmay be replaced and/or supplemented by local area networks (LANs) designed to communicate data between devices located in a local area, such as a Wi-Fi network. The WAN and/or LANs typically include computer hardware such as copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and edge servers.

END USER DEVICE (EUD)is any computer system that is used and controlled by an end user (for example, a customer of an enterprise that operates computer), and may take any of the forms discussed above in connection with computer. EUD, which may include the components of clientin, typically receives helpful and useful data from the operations of computer. For example, in a hypothetical case where computeris designed to provide a recommendation to an end user, this recommendation would typically be communicated from network moduleof computerthrough WANto EUD. In this way, EUDcan display, or otherwise present, the recommendation to an end user. In some embodiments, EUDmay be a client device, such as thin client, heavy client, mainframe computer, desktop computer and so on.

REMOTE SERVERis any computer system that serves at least some data and/or functionality to computer. Remote servermay be controlled and used by the same entity that operates computer. Remote serverrepresents the machine(s) that collect and store helpful and useful data for use by other computers, such as computer. For example, in a hypothetical case where computeris designed and programmed to provide a recommendation based on historical data, then this historical data may be provided to computerfrom remote databaseof remote server.

PUBLIC CLOUDis any computer system available for use by multiple entities that provides on-demand availability of computer system resources and/or other computer capabilities, especially data storage (cloud storage) and computing power, without direct active management by the user. Cloud computing typically leverages sharing of resources to achieve coherence and economies of scale. The direct and active management of the computing resources of public cloudis performed by the computer hardware and/or software of cloud orchestration module. The computing resources provided by public cloudare typically implemented by virtual computing environments that run on various computers making up the computers of host physical machine set, which is the universe of physical computers in and/or available to public cloud. The virtual computing environments (VCEs) typically take the form of virtual machines from virtual machine setand/or containers from container set. It is understood that these VCEs may be stored as images and may be transferred among and between the various physical machine hosts, either as images or after instantiation of the VCE. Cloud orchestration modulemanages the transfer and storage of images, deploys new instantiations of VCEs and manages active instantiations of VCE deployments. Gatewayis the collection of computer software, hardware, and firmware that allows public cloudto communicate through WAN.

Some further explanation of virtualized computing environments (VCEs) will now be provided. VCEs can be stored as “images.” A new active instance of the VCE can be instantiated from the image. Two familiar types of VCEs are virtual machines and containers. A container is a VCE that uses operating-system-level virtualization. This refers to an operating system feature in which the kernel allows the existence of multiple isolated user-space instances, called containers. These isolated user-space instances typically behave as real computers from the point of view of programs running in them. A computer program running on an ordinary operating system can utilize all resources of that computer, such as connected devices, files and folders, network shares, CPU power, and quantifiable hardware capabilities. However, programs running inside a container can only use the contents of the container and devices assigned to the container, a feature which is known as containerization.

PRIVATE CLOUDis similar to public cloud, except that the computing resources are only available for use by a single enterprise. While private cloudis depicted as being in communication with WAN, in other embodiments a private cloud may be disconnected from the internet entirely and only accessible through a local/private network. A hybrid cloud is a composition of multiple clouds of different types (for example, private, community or public cloud types), often respectively implemented by different vendors. Each of the multiple clouds remains a separate and discrete entity, but the larger hybrid cloud architecture is bound together by standardized or proprietary technology that enables orchestration, management, and/or data/application portability between the multiple constituent clouds. In this embodiment, public cloudand private cloudare both part of a larger hybrid cloud.